Abstract:
Sarcomas, a diverse group of rare malignancies, pose significant diagnostic and prognostic challenges due to their heterogeneity and complex histopathology. The integration of artificial intelligence (AI) and digital pathology offers transformative potential in addressing these challenges. The rapidly evolving state-of-the-art AI-driven algorithms, leveraging deep learning and computer vision, can analyze high-resolution digital pathology images to enhance diagnostic accuracy, identify subtle morphological features, and predict clinical outcomes. This talk explores the role of AI in assisting subtyping, detecting biomarkers, and predicting prognosis in different sarcomas. By bridging the gap between pathology and AI, this emerging synergy promises to revolutionize sarcoma care, enabling precision medicine and improving patient outcomes.
